172 resultados para Algoritmo memético


Relevância:

10.00% 10.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

Relevância:

10.00% 10.00%

Publicador:

Resumo:

The increasing demand for high performance wireless communication systems has shown the inefficiency of the current model of fixed allocation of the radio spectrum. In this context, cognitive radio appears as a more efficient alternative, by providing opportunistic spectrum access, with the maximum bandwidth possible. To ensure these requirements, it is necessary that the transmitter identify opportunities for transmission and the receiver recognizes the parameters defined for the communication signal. The techniques that use cyclostationary analysis can be applied to problems in either spectrum sensing and modulation classification, even in low signal-to-noise ratio (SNR) environments. However, despite the robustness, one of the main disadvantages of cyclostationarity is the high computational cost for calculating its functions. This work proposes efficient architectures for obtaining cyclostationary features to be employed in either spectrum sensing and automatic modulation classification (AMC). In the context of spectrum sensing, a parallelized algorithm for extracting cyclostationary features of communication signals is presented. The performance of this features extractor parallelization is evaluated by speedup and parallel eficiency metrics. The architecture for spectrum sensing is analyzed for several configuration of false alarm probability, SNR levels and observation time for BPSK and QPSK modulations. In the context of AMC, the reduced alpha-profile is proposed as as a cyclostationary signature calculated for a reduced cyclic frequencies set. This signature is validated by a modulation classification architecture based on pattern matching. The architecture for AMC is investigated for correct classification rates of AM, BPSK, QPSK, MSK and FSK modulations, considering several scenarios of observation length and SNR levels. The numerical results of performance obtained in this work show the eficiency of the proposed architectures

Relevância:

10.00% 10.00%

Publicador:

Resumo:

We propose in this work a software architecture for robotic boats intended to act in diverse aquatic environments, fully autonomously, performing telemetry to a base station and getting this mission to be accomplished. This proposal aims to apply within the project N-Boat Lab NatalNet DCA, which aims to empower a sailboat navigating autonomously. The constituent components of this architecture are the memory modules, strategy, communication, sensing, actuation, energy, security and surveillance, making these systems the boat and base station. To validate the simulator was developed in C language and implemented using the graphics API OpenGL resources, whose main results were obtained in the implementation of memory, performance and strategy modules, more specifically data sharing, control of sails and rudder and planning short routes based on an algorithm for navigation, respectively. The experimental results, shown in this study indicate the feasibility of the actual use of the software architecture developed and their application in the area of autonomous mobile robotics

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Bayesian networks are powerful tools as they represent probability distributions as graphs. They work with uncertainties of real systems. Since last decade there is a special interest in learning network structures from data. However learning the best network structure is a NP-Hard problem, so many heuristics algorithms to generate network structures from data were created. Many of these algorithms use score metrics to generate the network model. This thesis compare three of most used score metrics. The K-2 algorithm and two pattern benchmarks, ASIA and ALARM, were used to carry out the comparison. Results show that score metrics with hyperparameters that strength the tendency to select simpler network structures are better than score metrics with weaker tendency to select simpler network structures for both metrics (Heckerman-Geiger and modified MDL). Heckerman-Geiger Bayesian score metric works better than MDL with large datasets and MDL works better than Heckerman-Geiger with small datasets. The modified MDL gives similar results to Heckerman-Geiger for large datasets and close results to MDL for small datasets with stronger tendency to select simpler network structures

Relevância:

10.00% 10.00%

Publicador:

Resumo:

This work considers the development of a filtering system composed of an intelligent algorithm, that separates information and noise coming from sensors interconnected by Foundation Fieldbus (FF) network. The algorithm implementation will be made through FF standard function blocks, with on-line training through OPC (OLE for Process Control), and embedded technology in a DSP (Digital Signal Processor) that interacts with the fieldbus devices. The technique ICA (Independent Component Analysis), that explores the possibility of separating mixed signals based on the fact that they are statistically independent, was chosen to this Blind Source Separation (BSS) process. The algorithm and its implementations will be Presented, as well as the results

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Navigation based on visual feedback for robots, working in a closed environment, can be obtained settling a camera in each robot (local vision system). However, this solution requests a camera and capacity of local processing for each robot. When possible, a global vision system is a cheapest solution for this problem. In this case, one or a little amount of cameras, covering all the workspace, can be shared by the entire team of robots, saving the cost of a great amount of cameras and the associated processing hardware needed in a local vision system. This work presents the implementation and experimental results of a global vision system for mobile mini-robots, using robot soccer as test platform. The proposed vision system consists of a camera, a frame grabber and a computer (PC) for image processing. The PC is responsible for the team motion control, based on the visual feedback, sending commands to the robots through a radio link. In order for the system to be able to unequivocally recognize each robot, each one has a label on its top, consisting of two colored circles. Image processing algorithms were developed for the eficient computation, in real time, of all objects position (robot and ball) and orientation (robot). A great problem found was to label the color, in real time, of each colored point of the image, in time-varying illumination conditions. To overcome this problem, an automatic camera calibration, based on clustering K-means algorithm, was implemented. This method guarantees that similar pixels will be clustered around a unique color class. The obtained experimental results shown that the position and orientation of each robot can be obtained with a precision of few millimeters. The updating of the position and orientation was attained in real time, analyzing 30 frames per second

Relevância:

10.00% 10.00%

Publicador:

Resumo:

There has been an increasing tendency on the use of selective image compression, since several applications make use of digital images and the loss of information in certain regions is not allowed in some cases. However, there are applications in which these images are captured and stored automatically making it impossible to the user to select the regions of interest to be compressed in a lossless manner. A possible solution for this matter would be the automatic selection of these regions, a very difficult problem to solve in general cases. Nevertheless, it is possible to use intelligent techniques to detect these regions in specific cases. This work proposes a selective color image compression method in which regions of interest, previously chosen, are compressed in a lossless manner. This method uses the wavelet transform to decorrelate the pixels of the image, competitive neural network to make a vectorial quantization, mathematical morphology, and Huffman adaptive coding. There are two options for automatic detection in addition to the manual one: a method of texture segmentation, in which the highest frequency texture is selected to be the region of interest, and a new face detection method where the region of the face will be lossless compressed. The results show that both can be successfully used with the compression method, giving the map of the region of interest as an input

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Due to advances in the manufacturing process of orthopedic prostheses, the need for better quality shape reading techniques (i.e. with less uncertainty) of the residual limb of amputees became a challenge. To overcome these problems means to be able in obtaining accurate geometry information of the limb and, consequently, better manufacturing processes of both transfemural and transtibial prosthetic sockets. The key point for this task is to customize these readings trying to be as faithful as possible to the real profile of each patient. Within this context, firstly two prototype versions (α and β) of a 3D mechanical scanner for reading residual limbs shape based on reverse engineering techniques were designed. Prototype β is an improved version of prototype α, despite remaining working in analogical mode. Both prototypes are capable of producing a CAD representation of the limb via appropriated graphical sheets and were conceived to work purely by mechanical means. The first results were encouraging as they were able to achieve a great decrease concerning the degree of uncertainty of measurements when compared to traditional methods that are very inaccurate and outdated. For instance, it's not unusual to see these archaic methods in action by making use of ordinary home kind measure-tapes for exploring the limb's shape. Although prototype β improved the readings, it still required someone to input the plotted points (i.e. those marked in disk shape graphical sheets) to an academic CAD software called OrtoCAD. This task is performed by manual typing which is time consuming and carries very limited reliability. Furthermore, the number of coordinates obtained from the purely mechanical system is limited to sub-divisions of the graphical sheet (it records a point every 10 degrees with a resolution of one millimeter). These drawbacks were overcome by designing the second release of prototype β in which it was developed an electronic variation of the reading table components now capable of performing an automatic reading (i.e. no human intervention in digital mode). An interface software (i.e. drive) was built to facilitate data transfer. Much better results were obtained meaning less degree of uncertainty (it records a point every 2 degrees with a resolution of 1/10 mm). Additionally, it was proposed an algorithm to convert the CAD geometry, used by OrtoCAD, to an appropriate format and enabling the use of rapid prototyping equipment aiming future automation of the manufacturing process of prosthetic sockets.

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Multiphase flows in ducts can adopt several morphologies depending on the mass fluxes and the fluids properties. Annular flow is one of the most frequently encountered flow patterns in industrial applications. For gas liquid systems, it consists of a liquid film flowing adjacent to the wall and a gas core flowing in the center of the duct. This work presents a numerical study of this flow pattern in gas liquid systems in vertical ducts. For this, a solution algorithm was developed and implemented in FORTRAN 90 to numerically solve the governing transport equations. The mass and momentum conservation equations are solved simultaneously from the wall to the center of the duct, using the Finite Volumes Technique. Momentum conservation in the gas liquid interface is enforced using an equivalent effective viscosity, which also allows for the solution of both velocity fields in a single system of equations. In this way, the velocity distributions across the gas core and the liquid film are obtained iteratively, together with the global pressure gradient and the liquid film thickness. Convergence criteria are based upon satisfaction of mass balance within the liquid film and the gas core. For system closure, two different approaches are presented for the calculation of the radial turbulent viscosity distribution within the liquid film and the gas core. The first one combines a k- Ɛ one-equation model and a low Reynolds k-Ɛ model. The second one uses a low Reynolds k- Ɛ model to compute the eddy viscosity profile from the center of the duct right to the wall. Appropriate interfacial values for k e Ɛ are proposed, based on concepts and ideas previously used, with success, in stratified gas liquid flow. The proposed approaches are compared with an algebraic model found in the literature, specifically devised for annular gas liquid flow, using available experimental results. This also serves as a validation of the solution algorithm

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Annular flow is the prevailing pattern in transport and energy conversion systems and therefore, one of the most important patterns in multiphase flow in ducts. The correct prediction of the pressure gradient and heat transfer coefficient is essential for optimizing the system s capacity. The objective of this work is to develop and implement a numerical algorithm capable of predicting hydrodynamic and thermal characteristics for upflow, vertical, annular flow. The numerical algorithm is then complemented with the physical modeling of phenomena that occurs in this flow pattern. These are, turbulence, entrainment and deposition and phase change. For the development of the numerical model, axial diffusion of heat and momentum is neglected. In this way the time-averaged equations are solved in their parabolic form obtaining the velocity and temperature profiles for each axial step at a time, together with the global parameters, namely, pressure gradient, mean film thickness and heat transfer coefficient, as well as their variation in the axial direction. The model is validated for the following conditions: fully-developed laminar flow with no entrainment; fully developed laminar flow with heat transfer, fully-developed turbulent flow with entrained drops, developing turbulent annular flow with entrained drops, and turbulent flow with heat transfer and phase change

Relevância:

10.00% 10.00%

Publicador:

Resumo:

The study of aerodynamic loading variations has many engineering applications, including helicopter rotor blades, wind turbines and turbo machinery. This work uses a Vortex Method to make a lagrangian description of the a twodimensional airfoil/ incident wake vortex interaction. The flow is incompressible, newtonian, homogeneus and the Reynolds Number is 5x105 .The airfoil is a NACA 0018 placed a angle of attack of the 0° and 5°simulates with the Painel Method with a constant density vorticity panels and a generation poit is near the painel. The protector layer is created does not permit vortex inside the body. The vortex Lamb convection is realized with the Euler Method (first order) and Adans-Bashforth (second order). The Random Walk Method is used to simulate the diffusion. The circular wake has 366 vortex all over positive or negative vorticity located at different heights with respect to the airfoil chord. The Lift was calculated based in the algorithm created by Ricci (2002). This simulation uses a ready algorithm vatidated with single body does not have a incident wake. The results are compared with a experimental work The comparasion concludes that the experimental results has a good agrement with this papper

Relevância:

10.00% 10.00%

Publicador:

Resumo:

One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoil

Relevância:

10.00% 10.00%

Publicador:

Resumo:

The present work has the main goal to study the modeling and simulation of a biphasic separator with induced phase inversion, the MDIF, with the utilization of the finite differences method for the resolution of the partial differencial equations which describe the transport of contaminant s mass fraction inside the equipment s settling chamber. With this aim, was developed the deterministic differential model AMADDA, wich was admensionalizated and then semidiscretizated with the method of lines. The integration of the resultant system of ordinary differential equations was realized by means of a modified algorithm of the Adam-Bashfort- Moulton method, and the sthocastic optimization routine of Basin-Hopping was used in the model s parameter estimation procedure . With the aim to establish a comparative referential for the results obtained with the model AMADDA, were used experimental data presented in previous works of the MDIF s research group. The experimental data and those obtained with the model was assessed regarding its normality by means of the Shapiro-Wilk s test, and validated against the experimental results with the Student s t test and the Kruskal-Wallis s test, depending on the result. The results showed satisfactory performance of the model AMADDA in the evaluation of the MDIF s separation efficiency, being possible to determinate that at 1% significance level the calculated results are equivalent to those determinated experimentally in the reference works

Relevância:

10.00% 10.00%

Publicador:

Resumo:

Expanded Bed Adsorption (EBA) is an integrative process that combines concepts of chromatography and fluidization of solids. The many parameters involved and their synergistic effects complicate the optimization of the process. Fortunately, some mathematical tools have been developed in order to guide the investigation of the EBA system. In this work the application of experimental design, phenomenological modeling and artificial neural networks (ANN) in understanding chitosanases adsorption on ion exchange resin Streamline® DEAE have been investigated. The strain Paenibacillus ehimensis NRRL B-23118 was used for chitosanase production. EBA experiments were carried out using a column of 2.6 cm inner diameter with 30.0 cm in height that was coupled to a peristaltic pump. At the bottom of the column there was a distributor of glass beads having a height of 3.0 cm. Assays for residence time distribution (RTD) revelead a high degree of mixing, however, the Richardson-Zaki coefficients showed that the column was on the threshold of stability. Isotherm models fitted the adsorption equilibrium data in the presence of lyotropic salts. The results of experiment design indicated that the ionic strength and superficial velocity are important to the recovery and purity of chitosanases. The molecular mass of the two chitosanases were approximately 23 kDa and 52 kDa as estimated by SDS-PAGE. The phenomenological modeling was aimed to describe the operations in batch and column chromatography. The simulations were performed in Microsoft Visual Studio. The kinetic rate constant model set to kinetic curves efficiently under conditions of initial enzyme activity 0.232, 0.142 e 0.079 UA/mL. The simulated breakthrough curves showed some differences with experimental data, especially regarding the slope. Sensitivity tests of the model on the surface velocity, axial dispersion and initial concentration showed agreement with the literature. The neural network was constructed in MATLAB and Neural Network Toolbox. The cross-validation was used to improve the ability of generalization. The parameters of ANN were improved to obtain the settings 6-6 (enzyme activity) and 9-6 (total protein), as well as tansig transfer function and Levenberg-Marquardt training algorithm. The neural Carlos Eduardo de Araújo Padilha dezembro/2013 9 networks simulations, including all the steps of cycle, showed good agreement with experimental data, with a correlation coefficient of approximately 0.974. The effects of input variables on profiles of the stages of loading, washing and elution were consistent with the literature